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COVERIF Project Meetings

Meeting 1 (4th April, 2016):Meeting 2 (23rd September, 2016):

Filling the gap between the standard splitting strategy and
MindTheGap

In Constraint Programming (CP), to solve a Constraint Satisfaction Problem (CSP),
solving methods alternate two phases: propagation and exploration. In continuous
solving, the propagation phase computes an over-approximation of the solutions and
the information that can be gathered during this phase are lost in the exploration
phase. We propose a new splitting strategy, relying on the propagation phase.

A Concoction of Zonotope Abstraction and Constraint Programming
for finding an Invariant

Synthesizing an invariant is a key concept in formal verification ensuring
correctness of programs and finding bugs, e.g., the program variables
staying within some bounds. The standard method for finding an invariant
is to look for inductive invariant, which is a stronger form of invariant.
This work deals with the challenges associated while combining abstract
interpretation (zonotopes) and constraint programming for infering
inductive invariants.

On finding program input values maximizing the rounding-off error
Evaluating expressions on floating point numbers can produce results which are far from the
expected result on real numbers. Such a behaviour is one of the main failures of programs
handling floating point numbers. We present a new method for generating a critical test cases.
Our method try to maximize the rounding error for a given expression using a greedy algorithm.
The bulk of our contribution is the maximization of the rounding error on elementary operations.